Getting into “Pivot: Eight Principles for Pivoting through Disruption” took me a while. Napster moments, the music industry, gatekeepers, the long tail, virality, Radiohead, Spotify, attention economics, gaming, sameness, farmers, builders, and disruption. The 6Ds from “Bold” . Digitisation leads to deception first, then disruption, then demonetisation, then dematerialisation and eventually to democratisation.
We are starting from the wrong baseline
A book about how our economic modelling is wrong. You need to re-consider surplus, network effects, monopolies, rationality, the economic units (money vs time and convenience), IP, mood, statistics, GDP, big data, and quantification bias. We are not a sum of data or an algorithm. You are not math, engineering, science. You are art, you are joy, you are soul, you are small data, you are intuition, you are quirky, messy, and you are amazing.
AI and humanity
With in the back of my mind always that AI is fed by big data. Data from the past. Also, realising that an AI can never feel the sunshine on its skin. Or feel music, or love or explain why the steak tartare in Malaga is better than the one in the restaurant in La Calla (and that the waiter is a main factor in that experience). That is why you will never watch robots play rugby. An AI will never understand Ireland vs England in rugby. AI will never appreciate life music. I digress. You should also read this.
Tarzan economics
Navigating disruption requires the confidence of knowing when to let go of old ideas and grab on to new ones. Tarzan economics. A long time ago, Tarzan was mentioned in “The business model innovation factory”. Swinging from the old to the new. How fear of the unknown has and will continue to lead to resistance to reach out to the new vine. The need to realise not only how fast-paced technological disruption is but also how unstable the status quo is – like a bicycle, it falls over if it doesn’t move forward.
Attention is interesting
Hooked” lists five forms of attention – watch, listen, play, read, and communicate. Music is a complementary form of attention. When we are binge-watching, we’re giving Netflix a monopoly on our attention. When we have to focus on one activity – like getting lost in a good book – we remember that our attention is limited and therefore scarce. There is no single measure of attention. Active attention (dwell time), passive attention (out of focus) and inferred attention (implied by behaviour). Not one of these metrics directly reflects value.
Language
The syntax matters. In English, we ‘pay’; in Spanish, we ‘lend’; in French, we ‘make’; and in Swedish, we ‘give’.The history of how we measure attention shows us that companies don’t just compete within their own industries – but with anyone or anything that might conceivably take up a consumer’s scarce time. For example, reading books eats into scarce attention – often resulting in a zero-sum game in which there is a clear winner (the object you spend your attention on) and a loser (everything else you could have spent your attention on). Netflix CEO Reed Hastings suggested that sleep was his biggest competitor.
Attention economics
With attention economics, it is important not only to maximise attention but also to do it efficiently. For example, one of Google’s core objectives for its search function is focused on how little (as opposed to how much) attention a user must pay before finding what they’re looking for. Less time spent searching means a better-performing search engine.
Gaming
One needs to look no further than the recent past of the gaming industry to see how the contestability of attention will play out in the future. Gaming has constantly had to innovate to win attention. What differentiates gaming from bingeing on Netflix is the amount of voluntary effort that is required to engage with the content and the gradual but certain advancement in skills that is an inherent part of most gaming experiences.
Fortnite
As the music industry celebrated reaching 341 million digital subscribers around the world after twenty years of blood, sweat, and tears, it needed to remember that Fortnite amassed 350 million users in just three years. Why are games winning? No form of media is designed to work with our scarce attention like games, which are built from scratch to accomplish longitudinal entertainment via effort and reward.
VR
This is where virtual reality (VR) games move to the fore, as they demand your undivided attention.VR is well placed to win the battle for attention as it has set its sights on becoming a ‘first-class experience’. Read “Our Next Reality“. Games are becoming as valuable as anything Hollywood can produce and will soon be drawing bigger crowds.
Asymmetric crowds
Nassim Nicholas Taleb discusses this in the chapter ‘The Most Intolerant Wins: The Dominance of the Stubborn Minority’ in his book “Skin in the Game”. Tarzan Economics promotes thinking less about individuals and more about how social networks connect people into a community. Taleb argues that society doesn’t evolve by consensus – in fact, only a few people are needed to disproportionately move the needle for the whole of it. All it takes is an asymmetry that prevents the few from sharing an experience with the many for the whole group to fall apart. And asymmetries are present in just about everything.
Common good
If creators can form membership groups based around models of patronage, they can kill three birds with one stone, drawing a crowd that intermediaries no longer draw. That is why we need to understand what it takes to form collectives and why it pays to act in the common good of its members. The benefits of collectives permeate many industries facing disruption. Universities could give up on their unique brand identity to pool their expertise to further a specialist academic discipline collectively (prioritising progress over prestige); shopping malls could compete on shopfronts but form collectives to provide click-and-collect (reducing friction to fend off Amazon); local governments could form collectives with an aligned recycling policy across regional borders (as opposed to each having their own, at times, contradictory approach).
The need for pivotal thinking
The bullet holes that mattered were the ones that stopped planes from returning home. The Air Force needed to focus not on the positive signals but on the negatives. The zeroes, not the ones. Pivotal thinking means looking beyond, over and around the obvious ways of thinking – swimming lessons, patching up the planes that come back – and finding ways to better understand the actual world where decisions need to be made. By contrast, pivotal thinking is about recognising that ‘the opposite of a good idea can also be a good idea’. Read “Alchemy: The Surprising Power of Ideas That Don’t Make Sense“.
Convenience as a currency
We need to teach ourselves to think differently. If we are taught that a traditional monopoly is a bad idea for reasons that have long since lost their relevance, then we need to think differently when faced with the oxymoron of today’s tech monopolies (there’s a lot more than one) who compete for convenience that didn’t exist before. We need to pivot from a world where the monopolist gain is the consumer’s pain, to one where the motive for competition is convenience and the gains are shared. Network effects drown out everything else, as convenience is the new currency.
Flywheels
Flywheels completely transform the ordinary logic of a business as they capture the way convenience scales with adoption. Businesses that have this flywheel dynamic build on themselves, getting stronger and stronger as they scale, just like a flywheel that builds up more speed as it spins faster. This dynamic has become a hallmark of Silicon Valley-style disruption. What makes flywheels work cannot typically be found in economics textbooks.
Surplus
To do this, let’s consider the textbook concept of surplus. But this model is antiquated. In contrast to the assumptions of traditional economics, digital platforms are not concerned with marginal cost; it doesn’t cost them any more to serve 101 customers than it does to serve 100. And unlike most businesses in the past, digital platforms produce network effects, a virtuous cycle wherein the more consumers that use the platform, the better and more convenient it becomes for those that use it. The more consumers that use a platform, the more surplus they receive. And the bigger the platform, the more producer surplus grows.
Modelling and irrationality
When consumers don’t behave like an economist’s economic model would have predicted, they often blame the consumer for being irrational. But pivotal thinking calls time on such arrogance and pulls back the curtain on why theory and reality have diverged. Pivotal thinking involves ‘learning by doing’, having the confidence to involve ourselves in the debate, rather than remain a bystander, and to actually affect the outcomes.
Bismal science
It does no harm to inject a healthy dose of scepticism into the state of economics, be it the robustness of government data or the reliability of big data. My favourite book about GDP is “Buddhist economics“. Here are a few other things to consider from the book
- GDP is based on what people pay for goods and services. If something is free, it is not counted in GDP. Facebook and Google are two of the largest companies in the world, and their flagship products – Facebook’s social media platform and Google’s search platform – cost zero.
- How are global online retailers captured in GDP?
- Inflation is calculated based on the change in the cost of a selected basket of ‘typical’ goods. But how do economists decide what qualifies as ‘typical’ goods?
- The best illustration is the rise of ‘cloud storage’ – individuals, firms and governments are powering down their own local servers and adopting cloud services for their data-storage infrastructure.
- Academics determined that US Facebook users derived $231 billion in value from the platform between 2004 and 2019 – that’s $231 billion in value that bypasses the transactional measure of the economy.
- The contribution to the US economy from the creation of the smartphone is minimal, as the ‘value added’ part is allocated to its manufacturing base in Taiwan or South Korea despite it transforming the lives of a quarter of a billion American citizens.
- The contribution to the economy of having a car crash has a positive multiplier effect as you have used the measurable output of emergency services, insurance markets and (even) the production and consumption of a replacement car.
The system is broken. The digital economy is everywhere except in government statistics. The MIT team has ambitiously suggested a new measure of the economy that captures this surplus, with a new acronym: GDP-B (the B standing for Benefits).
Big data, big mistakes
We measure what is easy to measure. That is okay as far as it goes. We disregard that which can’t be easily measured or to give it an arbitrary quantitative value. That is artificial and misleading. And we presume that what can’t be measured easily really isn’t important. That is blindness. ‘The term “Big Data,” which spans economics, statistics and computer science, probably originated in lunch-table conversations at Silicon Graphics Inc. (SGI) in the mid-1990s. For data to be considered big, it needs to be big enough to be capable of causing a big problem – quantification bias. Quantification bias favours the measurable over the immeasurable and disregards what can’t be measured as unimportant (or, worse, non-existent). Quantification bias is a problem because it prioritises actions that generate data, as these are considered more valuable than ones that do not. Quantification bias favours measurable achievements over immeasurable preventions.
Small data
However, to avoid big data from causing big mistakes, we must take a step back and spot the problems that this explosion of big data can bring. Personally, I am a big fan of anthropology, which I think is the last mile of data. Read “Small data“. You can call it notable data or thick data. The data is at the opposite end of the spectrum and aims to capture the most direct, unmediated data from humans and the full context of their emotions and stories by – wait for it – meeting them. Like ethnography, qualitative data, or sensible thinking. This means rescuing precious data like human emotions, personal circumstances, and cultural traits that cannot be quantified, as well as rescuing the human context that big data can’t collect. For every data scientist being deployed to make sense of what they can (only) measure, ask how much resource is being deployed to ethnography, cultural awareness or simply engaging the consumer. Better still, talk to the actual customers and stop reducing them to data points.
Data is always the past
Don’t be caught up in herd-like mentality when it comes to data. You should never forget that it all comes from the same place: the past. Tarzan, in this instance, doesn’t always swing to the next tree as we’ve learned that the danger with big data is that people assume it to be always true, when, in fact, unless it’s understood properly, data proves to be a more compelling liar than even the most gifted of thieves.
Embrace Tarzan economics
As we all find ourselves staring at our Napster moment, we need to embrace Tarzan Economics in order to address life’s challenges sooner rather than later, as delay only means the problems get bigger and harder to solve.
